Data Science & Machine Learning Using Python
Lecture 21: Bias vs Variance In Machine Learning
Lecture 22: Ensemble Learning – Bagging
Lecture 23: Introduction (Real Estate Price Prediction Project)
Lecture 24: Data Cleaning (Real Estate Price Prediction Project)
Lecture 25: Feature Engineering (Real Estate Price Prediction)
Lecture 26: Outlier Removal (Real Estate Price Prediction Project)
Lecture 27: Model Building (Real Estate Price Prediction Project)
Lecture 28: Python Flask Server (Real Estate Price Prediction)
Lecture 29: Website or UI (Real Estate Price Prediction Project)
Lecture 30: Deploy machine learning model to production AWS (Amazon EC2 instance)
Lecture 31: Part 1 Introduction | Image Classification
Lecture 32: Part 2 Data Collection | Image Classification
Lecture 33: Part 3 Data Cleaning | Image Classification
Lecture 34: Part 4 Feature Engineering | Image Classification
Lecture 35: Part 5 Training a Model | Image Classification
Lecture 36: Part 6 Flask Server | Image Classification
Lecture 37: Part 7 Build Website | Image Classification
Lecture 38: Part 8 Deployment & Exercise | Image Classification
Lecture 39: What is feature engineering
Lecture 40: Outlier detection and removal using percentile
2 of 3
Previous Lesson
Next Lesson
Lecture 30: Deploy machine learning model to production AWS (Amazon EC2 instance)
Data Science & Machine Learning Using Python
Lecture 30: Deploy machine learning model to production AWS (Amazon EC2 instance)
Lecture 30: Deploy machine learning model to production AWS (Amazon EC2 instance)
Previous Lesson
Back to Course
Next Lesson
Scroll to top
Scroll to top
Login
Accessing this course requires a login. Please enter your credentials below!
Username or Email Address
Password
Remember Me
Lost Your Password?
Register
Don't have an account? Register one!
Register an Account